1. Field of the Invention
The present invention relates to a roll mark inspection apparatus for inspecting periodic roll marks (periodic defects) formed on a belt-like running material, such as a steel strip, an aluminum strip, or a copper strip, due to a roll surface speck existing on a reduction roll in rolling lines.
2. Description of the Related Art
In rolling lines, periodic roll marks are sometimes formed by a specked roll on a belt-like running material or a material to be rolled. In a press line using a plurality of rolls having different diameters, roll marks having different periods are formed on a material to be rolled.
A technique for inspecting each periodic roll mark is disclosed in Japanese Pat. Disclosure (Kokai) No. 58-156842. In this technique, an autocorrelation function of roll mark data is calculated to inspect each periodic roll mark. A principle of the technique will be described below. As shown in FIG. 4A, belt-like running material (to be referred to as a strip hereinafter) 2 to be rolled by roll 1 runs in an arrow direction and is wound at its terminal end to become coil 3.
In this process, if specks exist on the surface of roll 1, roll marks are formed on the surface of strip 2, and signals 4 (FIG. 4B), representing the roll marks, have a periodicity. FIG. 5A shows how the roll mark is produced. In FIG. 5B, reference symbol SA represents roll mark signals formed across an entire width of strip 2. In FIG. 5C, reference symbol SB represents roll mark signals formed on 1/8 of the entire width. Arrows ".dwnarw." represent roll mark signals to be inspected which apparently have periodicity. Other lines represent signals of random marks. Interval .tau. between arrows ".dwnarw." is equal to the circumferential length of roll 1.
Autocorrelation function .phi. of the roll mark signal (SA or SB) has a high peak at period .tau. (timing T1 in FIG. 6) corresponding to the circumferential length of roll 1. Therefore, the periodicity of roll marks to be inspected can be accurately detected by examining this peak.
FIG. 7 is a histogram showing the roll mark signals (SA or SB) obtained at each time interval .DELTA.t. Assuming that the envelope of the histogram is function f(t) of time t, then autocorrelation function .phi.(.tau.) is given by either of the following equations: ##EQU1## where T is an interval for obtaining the autocorrelation function.
More specifically, the autocorrelation function is calculated as follows: ##EQU2## On the basis of the above equation (3), calculations are repeatedly performed for each instantaneous time interval .DELTA.t while variables m and n are changed from 1 to M and from 0 to N, respectively, as follows: ##EQU3## In the above equations, the autocorrelation can be obtained by calculating a product of a roll mark signal preceded by circumferential length M.multidot..DELTA.t of roll 1 each time strip 2 advances by .DELTA.t, and by adding this product to a preceding calculated value, as represented by the equations (4-0) to (4-N) Then, the obtained autocorrelation is compared with a predetermined set value (roll mark detection level L) to inspect each periodic roll mark.
As a result, all the periodic roll marks formed by various rolls having roll specks can be simultaneously inspected, while an S/N ratio of the roll mark signal can be largely increased.
In rolling lines, the production rate is very high, e.g. 30 tons/min. For this reason, if roll marks are formed on the surface of a strip and inspection of the roll mark is delayed even slightly, a large amount of defective products (strip) are manufactured. Therefore, a demand has arisen for an apparatus capable of rapidly inspecting the roll mark.
In order to inspect the roll mark by the above technique, however, considerably long inspection length T of, at least 1,000 m, is required. In some cases, several thousands meters are required.
Further, since considerably long inspection length T is required to inspect the roll mark, a time for inspecting the roll mark is prolonged.
In addition, as shown in FIG. 8A, a background power level of the autocorrelation function (.SIGMA..phi.) calculated from roll mark signal data is increased as interval .tau. for calculating the autocorrelation function is reduced, and the background power level is reduced as interval .tau. is increased. Accordingly, values of peaks 5 and 6, each representing the roll mark, are reduced as interval .tau. is increased (FIG. 8A shows that the height of peak 6 at long interval .tau. is lower than that of peak 5 at short interval .tau.).
Therefore, when the autocorrelation value of each of roll mark peaks 5 and 6 is compared with roll mark detection level L, if this level L is fixed as shown in FIG. 8A, roll mark 6 obtained at long interval .tau. cannot be inspected although roll mark 5 can be inspected as shown in FIG. 8B. In addition, in this case, background noises in the region of short interval .tau. (hatched area in FIG. 8A) are erroneously detected as if roll marks are involved therein.
As described above, the conventional technique is adversely affected by the background power level (noise) and cannot therefore always inspect all roll marks having different periods.